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Optimization and Data Analysis in Biomedical Informatics pp 131–151Cite as

An Introduction to the Analysis of Functional Magnetic Resonance Imaging Data

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Part of the book series: Fields Institute Communications ((FIC,volume 63))

Abstract

Functional magnetic resonance imaging (fMRI) is a brain imaging technology primarily used to investigate how cognitive processes affect neural activity. Due to its non-invasiveness and high spatial resolution, this technology has quickly become one of the most important research tools in cognitive neuroscience and has played a growing role in a number of clinical applications. The interpretation of the results of an fMRI experiment involves the analysis of massive amounts of noisy, complex, multivariate data, resolved both spatially and temporally. The extraction of information from this data is a difficult and articulated task, which relies on methodologies lying at the intersection between image processing, statistics, and machine learning. We here introduce the reader to the rich and diverse literature in the fascinating field of fMRI data analysis, providing an overview of its main challenges and of the most common approaches to overcome them.

Mathematics Subject Classification (2010): Primary 54C40, 14E20, Secondary 46E25, 20C20

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Author information

Authors and Affiliations

  1. Rutgers Center for Operations Research, Rutgers University, Piscataway, NJ, 08854-8003, USA

    Gianluca Gazzola

  2. Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, 98115, USA

    Chun-An Chou

  3. Rutgers Center for Operations Research and Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, 08854, USA

    Myong K. Jeong

  4. Departments of Industrial and Systems Engineering and Radiology, University of Washington, Seattle, WA, 98195, USA

    W. Art Chaovalitwongse

Authors
  1. Gianluca Gazzola
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  2. Chun-An Chou
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  3. Myong K. Jeong
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  4. W. Art Chaovalitwongse
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Correspondence to W. Art Chaovalitwongse .

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Editors and Affiliations

  1. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611, Florida, USA

    Panos M. Pardalos

  2. , Department of Mathematics, University of Waterloo, University Avenue West 200, Waterloo, N2L 3G1, Ontario, Canada

    Thomas F. Coleman

  3. , Department of Industrial Engineering, University of Central Florida, Central Florida Blvd 4000, Orlando, 32816, Florida, USA

    Petros Xanthopoulos

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Gazzola, G., Chou, CA., Jeong, M.K., Chaovalitwongse, W.A. (2013). An Introduction to the Analysis of Functional Magnetic Resonance Imaging Data. In: Pardalos, P., Coleman, T., Xanthopoulos, P. (eds) Optimization and Data Analysis in Biomedical Informatics. Fields Institute Communications, vol 63. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4133-5_7

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